'Stata' presentation slideshows

Generalized Linear Models Classification

Generalized Linear Models Classification. SPH 247 Statistical Analysis of Laboratory Data. Generalized Linear Models . The type of predictive model one uses depends on a number of issues; one is the type of response.

1.03k views • 69 slides

STATA I: An Introduction Into the Basics

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Introduction to Data Analysis. March 31, 2008

645 views • 53 slides

Differential Item Functioning

Differential Item Functioning. Laura Gibbons, PhD Thank you, Rich Jones, Frances Yang, and Paul Crane. Thank you, NIA.

761 views • 47 slides

1.14k views • 40 slides

Dudley L. Poston, Jr. Texas A&M University & Eugenia Conde Rutgers University

Approaches for Addressing Issues of Missing Data in the Statistical Modeling of Adolescent Fertility. Dudley L. Poston, Jr. Texas A&M University & Eugenia Conde Rutgers University. Missing Data. Missing data are a pervasive challenge in scientific research.

449 views • 35 slides

Stata 12 Merging Guide

Stata 12 Merging Guide. Nathan Favero Texas A&M University October 19, 2012. Contents. Best Practices, pg. 3 Using Merge & Append, pg. 4 Merge, pg. 11 Append, pg. 14 Other Useful Commands, pg. 15 Importing Data into Stata , pg. 20 Delimited Files: Importing Variable Names, pg. 20

590 views • 29 slides

Poisson Regression Analysis

Poisson Regression Analysis. Analysis of rates and/or counts. Poisson Regression Analysis Data structure. Thus far we have discussed models for continuous data and for binary data. Poisson Regression Analysis Data structure.

2.56k views • 24 slides

Multiple Regression Analysis

Multiple Regression Analysis. y = b 0 + b 1 x 1 + b 2 x 2 + . . . b k x k + u 6. Heteroskedasticity. What is Heteroskedasticity. Recall the assumption of homoskedasticity implied that conditional on the explanatory variables, the variance of the unobserved error, u , was constant

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ASSUMPTION CHECKING

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AMMBR from xtreg to xtmixed (+checking for normality, random slopes)

AMMBR from xtreg to xtmixed (+checking for normality, random slopes). xtreg (with assumption checking). We knew already . We have the standard regression model (here with only one x): . but think that the data are clustered, and that the intercept (c 0 ) might be different

300 views • 18 slides

Sociology 601 Lecture 11: October 6, 2009

Sociology 601 Lecture 11: October 6, 2009. No office hours Oct. 15, but available all day Oct. 16 Homework Contingency Tables for Categorical Variables (8.1) some useful probabilities and hypothesis tests based on contingency tables independence redefined.

267 views • 15 slides

Stephen L. DesJardins Professor Center for the Study of Higher and Postsecondary Education

268 views • 14 slides

Gender Segregation by Occupation in the U.S.

Paige Hehl , UW Eau Claire Faculty Mentor: Dr. David Schaffer. Gender Segregation by Occupation in the U.S. . Previous Research.

251 views • 14 slides

Accessing Longitudinal Data via the Economic and Social Data Service Jack Kneeshaw 11 July 2006

ESDS Longitudinal. Accessing Longitudinal Data via the Economic and Social Data Service Jack Kneeshaw 11 July 2006. Economic and Social Data Service. provides access and support for key economic and social data

289 views • 13 slides

EDUC 200C Two sample t-tests

EDUC 200C Two sample t-tests. November 9, 2010. Review : What are the following?. Sampling Distribution Standard Error of the Mean Central Limit Theorem Confidence Interval Standard Error of the difference between the means Pooled variance.

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Fixed Effects Estimation

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Introducing the 1996 Canadian Food Expenditure Survey

Introducing the 1996 Canadian Food Expenditure Survey . For All Your Research Needs!. What is the 1996 Food Expenditure Survey? . Survey of household food expenditures over the 1996 period Participants kept a diary for two weeks Food expenditures included: groceries, fast food, restaurants.

244 views • 8 slides

Problem Set 1

Problem Set 1. Troubleshooting. Log Files. Save in text format for readability: l og using ps1 .log , replace o r: log using ps1, text. Handling Missing Values. By default, Stata excludes all observations marked with a period (.) from subsequent statistical analysis. Best practices:

176 views • 6 slides